Decathlon

The Medical Segmentation Decathlon challenge tests the generalisability of machine learning algorithms when applied to 10 different semantic segmentation task.

RibFrac

Rib Fracture Detection and Classification Challenge: A large-scale benchmark of 660 CT scans with ~5,000 rib fractures (around 80Gb)

Learn2Reg

Challenge on medical image registration addressing: learning from small datasets; estimating large deformations; dealing with multi-modal scans; and learning from noisy annotations

LoDoPaB-CT

Low-Dose CT reconstruction in the setting of the LoDoPaB-CT dataset.

COVID-19 LUNG CT LESION SEGMENTATION CHALLENGE - 2020

This challenge will create the platform to evaluate emerging methods for the segmentation and quantification of lung lesions caused by SARS-CoV-2 infection from CT images.

RealNoiseMRI

Brain MRI reconstruction challenge with realistic noise

SARAS-MESAD

This challenge is organized under MICCAI 2021, the 24th International Conference on Medical Image Computing and Computer Assisted Intervention. The event will be held from September 27th to October 1st 2021 in Strasbourg, France. The challenge focuses on multi-domain surgeon action detection.

The PI-CAI Challenge

Artificial Intelligence and Radiologists at Prostate Cancer Detection in MRI

SynthRAD2023

SynthRAD is the first challenge on automatic generation of synthetic computed tomography (sCT) for radiotherapy

Multi-Modality Abdominal Multi-Organ Segmentation Challenge 2022

Multi-site, Multi-Domain Airway Tree Modeling (ATM’22)

Airway segmentation is a crucial step for the analysis of pulmonary diseases including asthma, bronchiectasis, and emphysema. The accurate segmentation based on X-Ray computed tomography (CT) enables the quantitative measurements of airway dimensions and wall thickness, which can reveal the abnormality of patients with chronic obstructive pulmonary disease (COPD). Besides, the extraction of patient-specific airway models from CT images is required for navigatiisted surgery.

Shifts Challenge 2022

The goal of the Shifts Challenge 2022 is to raise awareness among the research community about the problems of distributional shift, robustness, and uncertainty estimation, and to identify new solutions to address them. The competition will consist of two new tracks: White Matter Multiple Sclerosis (MS) lesion segmentation in 3D Magnetic Resonance Imaging (MRI) of the brain and Marine cargo vessel power estimation.

Breast Cancer Immunohistochemical Image Generation Challenge

The Breast Cancer Immunohistochemical Image Generation Challenge aims to directly generate IHC-stained breast cancer histopathology images from HE-stained images.

The Head and Neck Organ-at-Risk CT & MR Segmentation Challenge

A semantic multimodal segmentation challenge comprising 30 organs at risk

ARCADE-MICCAI2023

Foundation Model Prompting for Medical Image Classification

The primary objective of this challenge is to promote the development and evaluation of model adaptation techniques for medical image classification to leverage the existing foundation models.

DENTEX - MICCAI23

Dental Enumeration and Diagnosis on Panoramic X- rays Challenge

Topology-Aware Anatomical Segmentation of the Circle of Willis

Segment the Circle of Willis (CoW) vessel components for both CTA and MRA

CL-Detection 2023

Cephalometric landmark detection in lateral x-ray images